Maximizing and evaluating the impact of test-trace-isolate programs: A modeling study.
PLoS Med
; 18(4): e1003585, 2021 04.
Article
in English
| MEDLINE | ID: covidwho-1209521
Preprint
This scientific journal article is probably based on a previously available preprint. It has been identified through a machine matching algorithm, human confirmation is still pending.
See preprint
This scientific journal article is probably based on a previously available preprint. It has been identified through a machine matching algorithm, human confirmation is still pending.
See preprint
ABSTRACT
BACKGROUND:
Test-trace-isolate programs are an essential part of coronavirus disease 2019 (COVID-19) control that offer a more targeted approach than many other nonpharmaceutical interventions. Effective use of such programs requires methods to estimate their current and anticipated impact. METHODS ANDFINDINGS:
We present a mathematical modeling framework to evaluate the expected reductions in the reproductive number, R, from test-trace-isolate programs. This framework is implemented in a publicly available R package and an online application. We evaluated the effects of completeness in case detection and contact tracing and speed of isolation and quarantine using parameters consistent with COVID-19 transmission (R0 2.5, generation time 6.5 days). We show that R is most sensitive to changes in the proportion of cases detected in almost all scenarios, and other metrics have a reduced impact when case detection levels are low (<30%). Although test-trace-isolate programs can contribute substantially to reducing R, exceptional performance across all metrics is needed to bring R below one through test-trace-isolate alone, highlighting the need for comprehensive control strategies. Results from this model also indicate that metrics used to evaluate performance of test-trace-isolate, such as the proportion of identified infections among traced contacts, may be misleading. While estimates of the impact of test-trace-isolate are sensitive to assumptions about COVID-19 natural history and adherence to isolation and quarantine, our qualitative findings are robust across numerous sensitivity analyses.CONCLUSIONS:
Effective test-trace-isolate programs first need to be strong in the "test" component, as case detection underlies all other program activities. Even moderately effective test-trace-isolate programs are an important tool for controlling the COVID-19 pandemic and can alleviate the need for more restrictive social distancing measures.
Full text:
Available
Collection:
International databases
Database:
MEDLINE
Main subject:
Disease Outbreaks
/
Contact Tracing
/
COVID-19
/
Models, Theoretical
Type of study:
Diagnostic study
/
Experimental Studies
/
Observational study
/
Prognostic study
/
Qualitative research
Limits:
Humans
Language:
English
Journal:
PLoS Med
Journal subject:
Medicine
Year:
2021
Document Type:
Article
Affiliation country:
Journal.pmed.1003585
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